Vegetation density analysis in Banda Aceh city before and after the tsunami using satellite imagery data

Vegetation density in Banda Aceh is an important aspect of monitoring the recovery process after being hit by a tsunami on December 26, 2004. The tsunami disaster had a tremendous impact on Banda Aceh city, both physical and non-physical damage. As a result, a lot of vegetation was swept away by the tsunami waves. After the tsunami disaster, Banda Aceh City carried out rehabilitation and reconstruction to change the land cover. The increasing population growth in the city also has affected land cover. Changes in land use not following the spatial plan of the Banda Aceh can reduce the quality of the environment, e.g., reducing the vegetation density in some areas. This paper presents the utilization of Landsat 7 and Landsat 8 images to analyze the vegetation density in Banda Aceh city before dan after the tsunami in the last 15 years. This study aims to determine the ability of satellite imagery to detect vegetation density in Banda Aceh in designated years before and after the tsunami. This study uses the Normalized Difference Vegetation Index analysis to observe the trend of vegetation density in the Banda Aceh. Results show that the vegetation density in Banda Aceh City in 2004, 2005, 2009, 2015, and 2020 was dominated by low-density classes. Still, in 2015 and 2020, there was an increase in medium and high vegetation density classes. This finding shows the pattern of the vegetation density follows the progress of the recovery after 15 years hit by a tsunami.

Modeling The Mysterious Tsunami Swirls In The Northeast Coast Of Japan During The March 2011 Tohoku Earthquake

The formation of tsunami swirls near the coast is an obvious oceanographic phenomenon during the occurrence of giant submarine earthquakes and mega-tsunamis. Several tsunami vortices were generated during the Asian tsunami of 2004 and the great Japan tsunami of March 2011 which lasted for several hours.New models of tsunami generation and propagation are hereby proposed and were used to investigate the tsunami inception, propagation and associated formation of swirls in the eastern coast of Japan. The proposed generation model assumes that the tsunami was driven by current oscillations at the seabed induced by the submarine earthquake. The major aim of this study is to develop a tsunami model to simulate the occurrence of tsunami swirls. Specifically, this study attempts to simulate and understand the formation of the mysterious tsunami swirls in the northeast coast of Japan. In addition, this study determines the vulnerability of the Philippines to destructive tsunami waves that originate near Japan. A coarse resolution model was therefore developed in a relatively large area encompassing Japan Sea and the eastern Philippine Sea. On the other hand, a fine-resolution model was implemented in a small area off Sendai coast near the epicenter. The model result was compared with the tsunami record obtained from the National Data Buoy Center with relatively good agreement as far as the height and period of the tsunami are concerned. Furthermore, the fine-resolution model was able to simulate the occurrence of tsunami vortices off Sendai coast with various sizes that lasted for several hours.

Spatial Modeling of Tsunami Vortices in the Coastal Ocean

It is important to plan for potential tsunamis during the marine spatial planning process so that land uses may be modified or defensive infrastructure may be erected. Tsunami vortices had been observed during the occurrence and propagation of tsunami waves. Actual observations during the March 2011 Japan tsunami and the Indian Ocean tsunami of December 2004 showed the formation of vortices which lasted for several hours. The Palu tsunami of September 2018 in Indonesia also showed the formation of a tsunami vortex whose centre was photographed by a pilot and appeared as a deep hole in the ocean. Several vortices with various sizes lasted for several hours after the quake and they also generated a loud roar as the giant waves inundated low-lying coastal areas. This essay attempts to describe the development of a model that can explain the formation of tsunami vortices.

Disaster Management: Tsunami and Remote Sensing Technology

Remote sensing technology has changed the way disasters like earthquakes and tsunamis are detected, monitored, and mapped in recent years. This paper summarizes the general theoretical study of Tsunami generation, propagation, and its inundation for deep, intermediate, and coastal waters. Tsunami is a Japanese word, which is made up of two words: “tsu” means harbor, and “nami” means waves. It means that Tsunami is the coastal gravity waves, which propagate close to the coastline. This analysis presents a novel method to explore the effects of tsunami waves on coastal areas. The methodology includes remote sensing nearness examinations and alteration identification strategies in remote sensing to outline a number of support routes along the coast and divide them into four homogenous sub-regions. The adjustments in the land spread are then measured in these sub-regions when the tidal wave occurs. The proposed paper gives a more solid and exact method than ordinary strategies to assess spatial examples of harmful territories through various land qualities along the coastline. The generative phase of tsunami development comprises the creation of an early disruption at the surface of the ocean due to the earthquake-generated distortion on the seafloor. Various comparative studies are also carried out using spatial technology to examine tsunami routes around the globe, taking into account the most recent tsunami occurrences.

Probabilistic, high-resolution tsunami predictions in northern Cascadia by exploiting sequential design for efficient emulation

The potential of a full-margin rupture along the Cascadia subduction zone poses a significant threat over a populous region of North America. Previous probabilistic tsunami hazard assessment studies produced hazard curves based on simulated predictions of tsunami waves, either at low resolution or at high resolution for a local area or under limited ranges of scenarios or at a high computational cost to generate hundreds of scenarios at high resolution. We use the graphics processing unit (GPU)-accelerated tsunami simulator VOLNA-OP2 with a detailed representation of topographic and bathymetric features. We replace the simulator by a Gaussian process emulator at each output location to overcome the large computational burden. The emulators are statistical approximations of the simulator's behaviour. We train the emulators on a set of input–output pairs and use them to generate approximate output values over a six-dimensional scenario parameter space, e.g. uplift/subsidence ratio and maximum uplift, that represent the seabed deformation. We implement an advanced sequential design algorithm for the optimal selection of only 60 simulations. The low cost of emulation provides for additional flexibility in the shape of the deformation, which we illustrate here considering two families – buried rupture and splay-faulting – of 2000 potential scenarios. This approach allows for the first emulation-accelerated computation of probabilistic tsunami hazard in the region of the city of Victoria, British Columbia.

Fast High-Resolution S-PTHA Along the Western Mediterranean Sea Coastlines. Application to the Bay of Cannes

Probabilistic Tsunami Hazard Assessment (PTHA) is a fundamental framework for producing time-independent forecasts of tsunami hazards at the coast, taking into account local to distant tsunamigenic earthquake sources. If high resolution bathymetry and topography data at the shoreline are available, local tsunami inundation models can be computed to identify the highest risk areas and derive evidence-based evacuation plans to improve community safety. We propose a fast high-resolution Seismic-PTHA approach to estimate the tsunami hazard at a coastal level using the Bay of Cannes as test site. The S-PTHA process is firstly fastened by performing seismic and tsunami hazards separately to allow for quick updates, either from seismic rates by adding new earthquakes, or from tsunami hazard by adding new scenarios of tsunamis. Furthermore, significant tsunamis are selected on the basis of the extrapolation of a tsunami amplitude collected offshore from low-resolution simulations to an a priori amplitude nearshore using Green’s law. This allows a saving in computation time on high-resolution simulations of almost 85%. The S-PTHA performed in the Bay of Cannes exhibits maximum expected tsunami waves that do not exceed 1 m in a 2500-year period, except in some particular places such as the Old Port of Cannes. However, the probability to experience wave heights of 30 cm in this same period exceeds 50% along the main beach of Cannes and these results need to be considered in risk mitigation plans given the high touristic attraction of the area, especially in summer times.

The May 2, 2020, Crete tsunami: comparison between registered and modelled mareograms

The Eastern Mediterranean and Aegean Sea are susceptible to strong earthquakes and tsunami waves. On May 2, 2020 a strong shock with Mw6.6 induced tsunami that was registered in the mareographic network. The tsunami did not cause inundations, but it was the reason to enforce a tsunami alert from the Tsunami Service Providers. Our study is focused on the tsunami numerical simulations of this event and the results are compared to the registered signals in the stations NOA-03 and NOA-04 in Kasos and Ierapetra.

Run! The Mountain Is Coming!

This chapter explains the dynamics of Glacier Lake Outburst Floods (GLOFs) or glacier tsunamis. It describes how climate change and resulting global warming is destabilizing high mountain glaciers perched above deep glacier lakes formed by receding glaciers and subsequent melting. The chapter goes on to explain how the collapse of large pieces of ice result in mountain top born tsunami waves that destroy downstream ecosystems, people, and infrastructure and how climate change is raising the likelihood that these glacier tsunamis will occur throughout the world. It recounts historical GLOF events throughout the world, detailing the impacts and risks of these tragic events.

Algorithmic Design of an FPGA-Based Calculator for Fast Evaluation of Tsunami Wave Danger

Events of a seismic nature followed by catastrophic floods caused by tsunami waves (the incidence of which has increased in recent decades) have an important impact on the populations of littoral regions. On the coast of Japan and Kamchatka, it takes nearly 20 min for tsunami waves to approach the nearest dry land after an offshore seismic event. This paper addresses an important question of fast simulation of tsunami wave propagation by mapping the algorithms in use in field-programmable gate arrays (FPGAs) with the help of high-level synthesis (HLS). Wave propagation is described by the shallow water system, and for numerical treatment the MacCormack scheme is used. The MacCormack algorithm is a direct difference scheme at a three-point stencil of a “cross” type; it happens to be appropriate for FPGA-based parallel implementation. A specialized calculator was designed. The developed software was tested for precision and performance. Numerical tests computing wave fronts show very good agreement with the available exact solutions (for two particular cases of the sea bed topography) and with the reference code. As the result, it takes just 17.06 s to simulate 1600 s (3200 time steps) of the wave propagation using a 3000 × 3200 computation grid with a VC709 board. The step length of the computational grid was chosen to display the simulation results in sufficient detail along the coastline. At the same time, the size of data arrays should provide their free placement in the memory of FPGA chips. The rather high performance achieved shows that tsunami danger could be correctly evaluated in a few minutes after seismic events.

Tsunami hazard in Lombok & Bali, Indonesia, due to the Flores backarc thrust

The tsunami hazard posed by the Flores backarc thrust, which runs along the northern coast of the islands of Bali and Lombok, Indonesia, is poorly studied compared to the Sunda megathrust, situated ~250 km to the south of the islands. However, the 2018 Lombok earthquake sequence demonstrated the seismic potential of the western Flores Thrust when a fault ramp beneath the island of Lombok ruptured in two Mw 6.9 earthquakes. Although the uplift in these events mostly occurred below land, the sequence still generated 1–2.5 m-high local tsunamis along the northern coast of Lombok (Wibowo et al., 2021). Historical records show that the Flores fault system in the Lombok and Bali region has generated at least six ≥ Ms 6.5 tsunamigenic earthquakes since 1800 CE. Hence, it is important to assess the possible tsunami hazard represented by this fault system. Here, we focus on the submarine fault segment located between the islands of Lombok and Bali (below the Lombok Strait). We assess modeled tsunami patterns generated by fault slip in six earthquake scenarios (slip of 1–5 m, representing Mw 7.2–7.9+), with a focus on impacts on the capital cities of Mataram, Lombok and Denpasar, Bali, which lie on the coasts facing the strait. We use a geologically constrained earthquake model informed by the Lombok earthquake sequence (Lythgoe et al., 2021), together with a high-resolution bathymetry dataset developed by combining direct measurements from GEBCO with sounding measurements from the official nautical charts for Indonesia. Our results show that fault rupture in this region could trigger a tsunami reaching Mataram in < 8 minutes and Denpasar in ~10–15 minutes, with multiple waves. For an earthquake with 3–5 m of coseismic slip, Mataram and Denpasar experience maximum wave heights of ~1.3–3.3 m and ~0.7 to 1.5 m, respectively. Furthermore, our earthquake models indicate that both cities would experience coseismic subsidence of 20–40 cm, exacerbating their exposure to both the tsunami and other coastal hazards. Overall, Mataram city is more exposed than Denpasar to high tsunami waves arriving quickly from the fault source. To understand how a tsunami would affect Mataram, we model the associated inundation using the 5 m slip model and show that Mataram is inundated ~55–140 m inland along the northern coast and ~230 m along the southern coast, with maximum flow depths of ~2–3 m. Our study highlights that the early tsunami arrival in Mataram, Lombok gives little time for residents to evacuate. Raising their awareness about the potential for locally generated tsunamis and the need for evacuation plans is important to help them respond immediately after experiencing strong ground shaking.